1 /*
2 * Licensed to the Apache Software Foundation (ASF) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * The ASF licenses this file to You under the Apache License, Version 2.0
6 * (the "License"); you may not use this file except in compliance with
7 * the License. You may obtain a copy of the License at
8 *
9 * http://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17 package org.apache.commons.math3.optim.univariate;
18
19 import org.apache.commons.math3.util.FastMath;
20 import org.apache.commons.math3.exception.NotStrictlyPositiveException;
21 import org.apache.commons.math3.optim.AbstractConvergenceChecker;
22
23 /**
24 * Simple implementation of the
25 * {@link org.apache.commons.math3.optimization.ConvergenceChecker} interface
26 * that uses only objective function values.
27 *
28 * Convergence is considered to have been reached if either the relative
29 * difference between the objective function values is smaller than a
30 * threshold or if either the absolute difference between the objective
31 * function values is smaller than another threshold.
32 * <br/>
33 * The {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)
34 * converged} method will also return {@code true} if the number of iterations
35 * has been set (see {@link #SimpleUnivariateValueChecker(double,double,int)
36 * this constructor}).
37 *
38 * @version $Id: SimpleUnivariateValueChecker.java 1462503 2013-03-29 15:48:27Z luc $
39 * @since 3.1
40 */
41 public class SimpleUnivariateValueChecker
42 extends AbstractConvergenceChecker<UnivariatePointValuePair> {
43 /**
44 * If {@link #maxIterationCount} is set to this value, the number of
45 * iterations will never cause
46 * {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)}
47 * to return {@code true}.
48 */
49 private static final int ITERATION_CHECK_DISABLED = -1;
50 /**
51 * Number of iterations after which the
52 * {@link #converged(int,UnivariatePointValuePair,UnivariatePointValuePair)}
53 * method will return true (unless the check is disabled).
54 */
55 private final int maxIterationCount;
56
57 /** Build an instance with specified thresholds.
58 *
59 * In order to perform only relative checks, the absolute tolerance
60 * must be set to a negative value. In order to perform only absolute
61 * checks, the relative tolerance must be set to a negative value.
62 *
63 * @param relativeThreshold relative tolerance threshold
64 * @param absoluteThreshold absolute tolerance threshold
65 */
66 public SimpleUnivariateValueChecker(final double relativeThreshold,
67 final double absoluteThreshold) {
68 super(relativeThreshold, absoluteThreshold);
69 maxIterationCount = ITERATION_CHECK_DISABLED;
70 }
71
72 /**
73 * Builds an instance with specified thresholds.
74 *
75 * In order to perform only relative checks, the absolute tolerance
76 * must be set to a negative value. In order to perform only absolute
77 * checks, the relative tolerance must be set to a negative value.
78 *
79 * @param relativeThreshold relative tolerance threshold
80 * @param absoluteThreshold absolute tolerance threshold
81 * @param maxIter Maximum iteration count.
82 * @throws NotStrictlyPositiveException if {@code maxIter <= 0}.
83 *
84 * @since 3.1
85 */
86 public SimpleUnivariateValueChecker(final double relativeThreshold,
87 final double absoluteThreshold,
88 final int maxIter) {
89 super(relativeThreshold, absoluteThreshold);
90
91 if (maxIter <= 0) {
92 throw new NotStrictlyPositiveException(maxIter);
93 }
94 maxIterationCount = maxIter;
95 }
96
97 /**
98 * Check if the optimization algorithm has converged considering the
99 * last two points.
100 * This method may be called several time from the same algorithm
101 * iteration with different points. This can be detected by checking the
102 * iteration number at each call if needed. Each time this method is
103 * called, the previous and current point correspond to points with the
104 * same role at each iteration, so they can be compared. As an example,
105 * simplex-based algorithms call this method for all points of the simplex,
106 * not only for the best or worst ones.
107 *
108 * @param iteration Index of current iteration
109 * @param previous Best point in the previous iteration.
110 * @param current Best point in the current iteration.
111 * @return {@code true} if the algorithm has converged.
112 */
113 @Override
114 public boolean converged(final int iteration,
115 final UnivariatePointValuePair previous,
116 final UnivariatePointValuePair current) {
117 if (maxIterationCount != ITERATION_CHECK_DISABLED && iteration >= maxIterationCount) {
118 return true;
119 }
120
121 final double p = previous.getValue();
122 final double c = current.getValue();
123 final double difference = FastMath.abs(p - c);
124 final double size = FastMath.max(FastMath.abs(p), FastMath.abs(c));
125 return difference <= size * getRelativeThreshold() ||
126 difference <= getAbsoluteThreshold();
127 }
128 }